Hierarchical Clustering of Hyperspectral Images using Rank-Two Nonnegative Matrix Factorization

14 Sep 2013 Nicolas Gillis Da Kuang Haesun Park

In this paper, we design a hierarchical clustering algorithm for high-resolution hyperspectral images. At the core of the algorithm, a new rank-two nonnegative matrix factorizations (NMF) algorithm is used to split the clusters, which is motivated by convex geometry concepts... (read more)

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